A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex

A multi-omic single-cell landscape of cellular diversification in the developing human cerebral cortex

The vast neuronal diversity in the human neocortex is vital for high-order brain functions, necessitating elucidation of the regulatory mechanisms underlying such unparalleled diversity. However, recent studies have yet to comprehensively reveal the diversity of neurons and the molecular logic of neocortical origin in humans at single-cell resolution through profiling transcriptomic or epigenomic landscapes, owing to the application of unimodal data alone to depict exceedingly heterogeneous populations of neurons. In this study, we generated a comprehensive compendium of the developing human neocortex by simultaneously profiling gene expression and open chromatin from the same cell. We computationally reconstructed the differentiation trajectories of excitatory projection neurons of cortical origin and inferred the regulatory logic governing lineage bifurcation decisions for neuronal diversification. We demonstrated that neuronal diversity arises from progenitor cell lineage specificity and postmitotic differentiation at distinct stages. Our data paves the way for understanding the primarily coordinated regulatory logic for neuronal diversification in the neocortex.

Single-cell RNA sequencing in diabetic kidney disease: a literature review

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease (ESRD), and its pathogenesis has not been clarified. Current research suggests that DKD involves multiple cell types and extra-renal factors, and it is particularly important to clarify the pathogenesis and identify new therapeutic targets. Single-cell RNA sequencing (scRNA-seq) technology is high-throughput sequencing of the transcriptomes of individual cells at the single-cell level, which is an effective technology for exploring the development of diseases by comparing genetic information, reflecting the differences in genetic information between cells, and identifying different cell subpopulations. Accumulating evidence supports the role of scRNA-seq in revealing the pathogenesis of diabetes and strengthening our understanding of the molecular mechanisms of DKD. We reviewed the scRNA-seq data this time. Then, we analyzed and discussed the applications of scRNA-seq technology in DKD research, including annotation of cell types, identification of novel cell types (or subtypes), identification of intercellular communication, analysis of cell differentiation trajectories, gene expression detection, and analysis of gene regulatory networks, and lastly, we explored the future perspectives of scRNA-seq technology in DKD research.

Single cell spatial biology over developmental time can decipher pediatric brain pathologies

Pediatric low grade brain tumors and neurodevelopmental disorders share proteins, signaling pathways, and networks. They also share germline mutations and an impaired prenatal differentiation origin. They may differ in the timing of the events and proliferation. We suggest that their pivotal distinct, albeit partially overlapping, outcomes relate to the cell states, which depend on their spatial location, and timing of gene expression during brain development. These attributes are crucial as the brain develops sequentially, and single-cell spatial organization influences cell state, thus function. Our underlying premise is that the root cause in neurodevelopmental disorders and pediatric tumors is impaired prenatal differentiation. Data related to pediatric brain tumors, neurodevelopmental disorders, brain cell (sub)types, locations, and timing of expression in the developing brain are scant. However, emerging single cell technologies, including transcriptomic, spatial biology, spatial high-resolution imaging performed over the brain developmental time, could be transformational in deciphering brain pathologies thereby pharmacology.

A single-cell transcriptomic landscape of cadmium-hindered brain development in mice

The effects of neurotoxicant cadmium (Cd) exposure on brain development have not been well elucidated. To investigate this, we have herein subjected pregnant mice to low-dose Cd throughout gestation. Using single-cell RNA sequencing (scRNA-seq), we explored the cellular responses in the embryonic brain to Cd exposure, and identified 18 distinct cell subpopulations that exhibited varied responses to Cd. Typically, Cd exposure impeded the development and maturation of cells in the brain, especially progenitor cells such as neural progenitor cells (NPCs) and oligodendrocyte progenitor cells (OPCs). It also caused significant cell subpopulation shifts in almost all the types of cells in the brain. Additionally, Cd exposure reduced the dendritic sophistication of cortical neurons in the offspring. Importantly, these changes led to aberrant Ca2+ activity in the cortex and neural behavior changes in mature offspring. These data contribute to our understanding of the effects and mechanisms of Cd exposure on brain development and highlight the importance of controlling environmental neurotoxicant exposure at the population level.

Molecular and cellular dynamics of the developing human neocortex at single-cell resolution

The development of the human neocortex is a highly dynamic process and involves complex cellular trajectories controlled by cell-type-specific gene regulation1. Here, we collected paired single-nucleus chromatin accessibility and transcriptome data from 38 human neocortical samples encompassing both the prefrontal cortex and primary visual cortex. These samples span five main developmental stages, ranging from the first trimester to adolescence. In parallel, we performed spatial transcriptomic analysis on a subset of the samples to illustrate spatial organization and intercellular communication. This atlas enables us to catalog cell type-, age-, and area-specific gene regulatory networks underlying neural differentiation. Moreover, combining single-cell profiling, progenitor purification, and lineage-tracing experiments, we have untangled the complex lineage relationships among progenitor subtypes during the transition from neurogenesis to gliogenesis in the human neocortex. We identified a tripotential intermediate progenitor subtype, termed Tri-IPC, responsible for the local production of GABAergic neurons, oligodendrocyte precursor cells, and astrocytes. Remarkably, most glioblastoma cells resemble Tri-IPCs at the transcriptomic level, suggesting that cancer cells hijack developmental processes to enhance growth and heterogeneity. Furthermore, by integrating our atlas data with large-scale GWAS data, we created a disease-risk map highlighting enriched ASD risk in second-trimester intratelencephalic projection neurons. Our study sheds light on the gene regulatory landscape and cellular dynamics of the developing human neocortex.

A novel TAp73-inhibitory compound counteracts stemness features of glioblastoma stem cells

Glioblastoma (GB) is the most common and fatal type of primary malignant brain tumor for which effective therapeutics are still lacking. GB stem cells, with tumor-initiating and self-renewal capacity, are mostly responsible for GB malignancy, representing a crucial target for therapies. The TP73 gene, which is highly expressed in GB, gives rise to the TAp73 isoform, a pleiotropic protein that regulates neural stem cell biology; however, its role in cancer has been highly controversial. We inactivated TP73 in human GB stem cells and revealed that TAp73 is required for their stemness potential, acting as a regulator of the transcriptional stemness signatures, highlighting TAp73 as a possible therapeutic target. As proof of concept, we identified a novel natural compound with TAp73-inhibitory capacity, which was highly effective against GB stem cells. The treatment reduced GB stem cell-invasion capacity and stem features, at least in part by TAp73 repression. Our data are consistent with a novel paradigm in which hijacking of p73-regulated neurodevelopmental programs, including neural stemness, might sustain tumor progression, pointing out TAp73 as a therapeutic strategy for GB.

Epigenomic landscapes during prefrontal cortex development and aging in rhesus

The prefrontal cortex (PFC) is essential for higher-level cognitive functions. How epigenetic dynamics participates in PFC development and aging is largely unknown. Here, we profiled epigenomic landscapes of rhesus monkey PFCs from prenatal to aging stages. The dynamics of chromatin states, including higher-order chromatin structure, chromatin interaction and histone modifications are coordinated to regulate stage-specific gene transcription, participating in distinct processes of neurodevelopment. Dramatic changes of epigenetic signals occur around the birth stage. Notably, genes involved in neuronal cell differentiation and layer specification are pre-configured by bivalent promoters. We identified a cis-regulatory module and the transcription factors (TFs) associated with basal radial glia development, which was associated with large brain size in primates. These TFs include GLI3, CREB5 and SOX9. Interestingly, the genes associated with the basal radial glia (bRG)-associated cis-element module, such as SRY and SOX9, are enriched in sex differentiation. Schizophrenia-associated single nucleotide polymorphisms are more enriched in super enhancers (SEs) than typical enhancers, suggesting that SEs play an important role in neural network wiring. A cis-regulatory element of DBN1 is identified, which is critical for neuronal cell proliferation and synaptic neuron differentiation. Notably, the loss of distal chromatin interaction and H3K27me3 signal are hallmarks of PFC aging, which are associated with abnormal expression of aging-related genes and transposon activation, respectively. Collectively, our findings shed light on epigenetic mechanisms underlying primate brain development and aging.

The Genetic Architecture of the Human Corpus Callosum and its Subregions

The corpus callosum (CC) is the largest set of white matter fibers connecting the two hemispheres of the brain. In humans, it is essential for coordinating sensorimotor responses, performing associative/executive functions, and representing information in multiple dimensions. Understanding which genetic variants underpin corpus callosum morphometry, and their shared influence on cortical structure and susceptibility to neuropsychiatric disorders, can provide molecular insights into the CC's role in mediating cortical development and its contribution to neuropsychiatric disease. To characterize the morphometry of the midsagittal corpus callosum, we developed a publicly available artificial intelligence based tool to extract, parcellate, and calculate its total and regional area and thickness. Using the UK Biobank (UKB) and the Adolescent Brain Cognitive Development study (ABCD), we extracted measures of midsagittal corpus callosum morphometry and performed a genome-wide association study (GWAS) meta-analysis of European participants (combined N = 46,685). We then examined evidence for generalization to the non-European participants of the UKB and ABCD cohorts (combined N = 7,040). Post-GWAS analyses implicate prenatal intracellular organization and cell growth patterns, and high heritability in regions of open chromatin, suggesting transcriptional activity regulation in early development. Results suggest programmed cell death mediated by the immune system drives the thinning of the posterior body and isthmus. Global and local genetic overlap, along with causal genetic liability, between the corpus callosum, cerebral cortex, and neuropsychiatric disorders such as attention-deficit/hyperactivity and bipolar disorders were identified. These results provide insight into variability of corpus callosum development, its genetic influence on the cerebral cortex, and biological mechanisms related to neuropsychiatric dysfunction.

Limitations of human brain organoids to study neurodegenerative diseases: a manual to survive

In 2013, M. Lancaster described the first protocol to obtain human brain organoids. These organoids, usually generated from human-induced pluripotent stem cells, can mimic the three-dimensional structure of the human brain. While they recapitulate the salient developmental stages of the human brain, their use to investigate the onset and mechanisms of neurodegenerative diseases still faces crucial limitations. In this review, we aim to highlight these limitations, which hinder brain organoids from becoming reliable models to study neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS). Specifically, we will describe structural and biological impediments, including the lack of an aging footprint, angiogenesis, myelination, and the inclusion of functional and immunocompetent microglia—all important factors in the onset of neurodegeneration in AD, PD, and ALS. Additionally, we will discuss technical limitations for monitoring the microanatomy and electrophysiology of these organoids. In parallel, we will propose solutions to overcome the current limitations, thereby making human brain organoids a more reliable tool to model neurodegeneration.

The Human Developing Cerebral Cortex Is Characterized by an Elevated De Novo Expression of Long Noncoding RNAs in Excitatory Neurons

The outstanding human cognitive capacities are computed in the cerebral cortex, a mammalian-specific brain region and the place of massive biological innovation. Long noncoding RNAs have emerged as gene regulatory elements with higher evolutionary turnover than mRNAs. The many long noncoding RNAs identified in neural tissues make them candidates for molecular sources of cerebral cortex evolution and disease. Here, we characterized the genomic and cellular shifts that occurred during the evolution of the long noncoding RNA repertoire expressed in the developing cerebral cortex and explored putative roles for these long noncoding RNAs in the evolution of the human brain. Using transcriptomics and comparative genomics, we comprehensively annotated the cortical transcriptomes of humans, rhesus macaques, mice, and chickens and classified human cortical long noncoding RNAs into evolutionary groups as a function of their predicted minimal ages. Long noncoding RNA evolutionary groups showed differences in expression levels, splicing efficiencies, transposable element contents, genomic distributions, and transcription factor binding to their promoters. Furthermore, older long noncoding RNAs showed preferential expression in germinative zones, outer radial glial cells, and cortical inhibitory (GABAergic) neurons. In comparison, younger long noncoding RNAs showed preferential expression in cortical excitatory (glutamatergic) neurons, were enriched in primate and human-specific gene co-expression modules, and were dysregulated in neurodevelopmental disorders. These results suggest different evolutionary routes for older and younger cortical long noncoding RNAs, highlighting old long noncoding RNAs as a possible source of molecular evolution of conserved developmental programs; conversely, we propose that the de novo expression of primate- and human-specific young long noncoding RNAs is a putative source of molecular evolution and dysfunction of cortical excitatory neurons, warranting further investigation.

Neurodegeneration and glial morphological changes are both prevented by TRPM2 inhibition during the progression of a Parkinson's disease mouse model

Parkinson's disease (PD) is a neurodegenerative disease characterized by dopaminergic neuron death and neuroinflammation. Emerging evidence points to the involvement of the transient receptor potential melastatin 2 (TRPM2) channel in neuron death and glial activation in several neurodegenerative diseases. However, the involvement of TRPM2 in PD and specifically its relation to the neuroinflammation aspect of the disease remains poorly understood. Here, we hypothesized that AG490, a TRPM2 inhibitor, can be used as a treatment in a mouse model of PD. Mice underwent stereotaxic surgery for 6-hydroxydopamine (6-OHDA) administration in the right striatum. Motor behavioral tests (apomorphine, cylinder, and rotarod) were performed on day 3 post-injection to confirm the PD model induction. AG490 was then daily injected i.p. between days 3 to 6 after surgery. On day 6, motor behavior was assessed again. Substantia nigra (SNc) and striatum (CPu) were collected for immunohistochemistry, immunoblotting, and RT-qPCR analysis on day 7. Our results revealed that AG490 post-treatment reduced motor behavior impairment and nigrostriatal neurodegeneration. In addition, the compound prevented TRPM2 upregulation and changes of the Akt/GSK-3β/caspase-3 signaling pathway. The TRPM2 inhibition also avoids the glial morphology changes observed in the PD group. Remarkably, the morphometrical analysis revealed that the ameboid-shaped microglia, found in 6-OHDA-injected animals, were no longer present in the AG490-treated group. These results indicate that AG490 treatment can reduce dopaminergic neuronal death and suppress neuroinflammation in a PD mouse model. Inhibition of TRPM2 by AG490 could then represent a potential therapeutical strategy to be evaluated for PD treatment.

Neural Differentiation and spinal cord organoid generation from induced pluripotent stem cells (iPSCs) for ALS modelling and inflammatory screening

C9orf72 genetic mutation is the most common genetic cause of ALS/FTD accompanied by abnormal protein insufficiency. Induced pluripotent stem cell (iPSC)-derived two-dimensional (2D) and three-dimensional (3D) cultures are providing new approaches. Therefore, this study established neuronal cell types and generated spinal cord organoids (SCOs) derived from C9orf72 knockdown human iPSCs to model ALS disease and screen the unrevealed phenotype. Wild-type (WT) iPSC lines from three healthy donor fibroblasts were established, and pluripotency and differentiation ability were identified by RT-PCR, immunofluorescence and flow cytometry. After infection by the lentivirus with C9orf72-targeting shRNA, stable C9-knockdown iPSC colonies were selected and differentiated into astrocytes, motor neurons and SCOs. Finally, we analyzed the extracted RNA-seq data of human C9 mutant/knockout iPSC-derived motor neurons and astrocytes from the GEO database and the inflammatory regulation-related genes in function and pathways. The expression of inflammatory factors was measured by qRT-PCR. The results showed that both WT-iPSCs and edited C9-iPSCs maintained a similar ability to differentiate into the three germ layers, astrocytes and motor neurons, forming SCOs in a 3D culture system. The constructed C9-SCOs have features of spinal cord development and multiple neuronal cell types, including sensory neurons, motor neurons, and other neurons. Based on the bioinformatics analysis, proinflammatory factors were confirmed to be upregulated in C9-iPSC-derived 2D cells and 3D cultured SCOs. The above differentiated models exhibited low C9orf72 expression and the pathological characteristics of ALS, especially neuroinflammation.

Deciphering brain cellular and behavioral mechanisms: Insights from single-cell and spatial RNA sequencing

The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single-cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single-cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep-wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single-cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease.

Genomic characteristics of adipose-derived stromal cells induced into neurons based on single-cell RNA sequencing

Adipose-derived stromal cells (ADSCs) can be induced to differentiate into neurons, representing the most promising avenue for cell therapy. However, the molecular mechanism and genomic characteristics of the differentiation of ADSCs into neurons remain poorly understood. In this study, cells from the adult ADSCs group, induction 1h, 3h, 5h, 6h, and 8h groups were selected for single-cell RNA sequencing (scRNA-Seq). Samples from these seven-time points were sequenced and analyzed. The expression of neuron marker genes, including NES, MAP2, TMEM59L, PTK2B, CHN1, DNM1, NRSN2, FBLN2, SCAMP1, SLC1A1, DLG4, CDK5, and ENO2, was found to be low in the ADSCs group, but highly expressed in differentiated cell clusters. The expression of stem cell marker genes, including CCND1, IL1B, MMP1, MMP3, MYO10, and BMP2, was the highest in the ADSCs cluster. This expression decreased significantly with the extension of induction time. Gene ontology (GO) enrichment analysis of upregulated genes in the induced samples showed that the biological processes related to neuronal differentiation and development, such as neuronal differentiation, projection, and apoptosis, were significantly upregulated with a longer induction time during cell cluster differentiation. The results of the cell communication analysis demonstrated the gradual formation of complex neural network connections between ADSC-derived neurons through receptor and ligand pairs at 5h after the induction of differentiation.

BrainTACO: an explorable multi-scale multi-modal brain transcriptomic and connectivity data resource

Exploring the relationships between genes and brain circuitry can be accelerated by joint analysis of heterogeneous datasets from 3D imaging data, anatomical data, as well as brain networks at varying scales, resolutions, and modalities. Generating an integrated view, beyond the individual resources' original purpose, requires the fusion of these data to a common space, and a visualization that bridges the gap across scales. However, despite ever expanding datasets, few platforms for integration and exploration of this heterogeneous data exist. To this end, we present the BrainTACO (Brain Transcriptomic And Connectivity Data) resource, a selection of heterogeneous, and multi-scale neurobiological data spatially mapped onto a common, hierarchical reference space, combined via a holistic data integration scheme. To access BrainTACO, we extended BrainTrawler, a web-based visual analytics framework for spatial neurobiological data, with comparative visualizations of multiple resources. This enables gene expression dissection of brain networks with, to the best of our knowledge, an unprecedented coverage and allows for the identification of potential genetic drivers of connectivity in both mice and humans that may contribute to the discovery of dysconnectivity phenotypes. Hence, BrainTACO reduces the need for time-consuming manual data aggregation often required for computational analyses in script-based toolboxes, and supports neuroscientists by directly leveraging the data instead of preparing it.

Unveiling novel cell clusters and biomarkers in glioblastoma and its peritumoral microenvironment at the single-cell perspective

BACKGROUND

Glioblastoma (GBM) is a highly heterogeneous, recurrent and aggressively invasive primary malignant brain tumor. The heterogeneity of GBM results in poor targeted therapy. Therefore, the aim of this study is to depict the cellular landscape of GBM and its peritumor from a single-cell perspective. Discovering new cell subtypes and biomarkers, and providing a theoretical basis for precision therapy.

METHODS

We collected 8 tissue samples from 4 GBM patients to perform 10 × single-cell transcriptome sequencing. Quality control and filtering of data by Seurat package for clustering. Inferring copy number variations to identify malignant cells via the infercnv package. Functional enrichment analysis was performed by GSVA and clusterProfiler packages. STRING database and Cytoscape software were used to construct protein interaction networks. Inferring transcription factors by pySCENIC. Building cell differentiation trajectories via the monocle package. To infer intercellular communication networks by CellPhoneDB software.

RESULTS

We observed that the tumor microenvironment (TME) varies among different locations and different GBM patients. We identified a proliferative cluster of oligodendrocytes with high expression of mitochondrial genes. We also identified two clusters of myeloid cells, one primarily located in the peritumor exhibiting an M1 phenotype with elevated TNFAIP8L3 expression, and another in the tumor and peritumor showing a proliferative tendency towards an M2 phenotype with increased DTL expression. We identified XIST, KCNH7, SYT1 and DIAPH3 as potential factors associated with the proliferation of malignant cells in GBM.

CONCLUSIONS

These biomarkers and cell clusters we discovered may serve as targets for treatment. Targeted drugs developed against these biomarkers and cell clusters may enhance treatment efficacy, optimize immune therapy strategies, and improve the response rates of GBM patients to immunotherapy. Our findings provide a theoretical basis for the development of individualized treatment and precision medicine for GBM, which may be used to improve the survival of GBM patients.

Gene regulatory landscape of cerebral cortex folding

Folding of the cerebral cortex is a key aspect of mammalian brain development and evolution, and defects are linked to severe neurological disorders. Primary folding occurs in highly stereotyped patterns that are predefined in the cortical germinal zones by a transcriptomic protomap. The gene regulatory landscape governing the emergence of this folding protomap remains unknown. We characterized the spatiotemporal dynamics of gene expression and active epigenetic landscape (H3K27ac) across prospective folds and fissures in ferret. Our results show that the transcriptomic protomap begins to emerge at early embryonic stages, and it involves cell-fate signaling pathways. The H3K27ac landscape reveals developmental cell-fate restriction and engages known developmental regulators, including the transcription factor Cux2. Manipulating Cux2 expression in cortical progenitors changed their proliferation and the folding pattern in ferret, caused by selective transcriptional changes as revealed by single-cell RNA sequencing analyses. Our findings highlight the key relevance of epigenetic mechanisms in defining the patterns of cerebral cortex folding.

Chronic Opioid Treatment Arrests Neurodevelopment and Alters Synaptic Activity in Human Midbrain Organoids

Understanding the impact of long-term opioid exposure on the embryonic brain is critical due to the surging number of pregnant mothers with opioid dependency. However, this has been limited by human brain inaccessibility and cross-species differences in animal models. Here, a human midbrain model is established that uses hiPSC-derived midbrain organoids to assess cell-type-specific responses to acute and chronic fentanyl treatment and fentanyl withdrawal. Single-cell mRNA sequencing of 25,510 cells from organoids in different treatment groups reveals that chronic fentanyl treatment arrests neuronal subtype specification during early midbrain development and alters synaptic activity and neuron projection. In contrast, acute fentanyl treatment increases dopamine release but does not significantly alter gene expression related to cell lineage development. These results provide the first examination of the effects of opioid exposure on human midbrain development at the single-cell level.

hPSC-Derived Astrocytes at the Forefront of Translational Applications in Neurological Disorders

Astrocytes, the most abundant glial cell type in the brain, play crucial roles in maintaining homeostasis within the central nervous system (CNS). Impairment or abnormalities of typical astrocyte functions in the CNS serve as a causative or contributing factor in numerous neurodevelopmental, neurodegenerative, and neuropsychiatric disorders. Currently, disease-modeling and drug-screening approaches, primarily focused on human astrocytes, rely on human pluripotent stem cell (hPSC)-derived astrocytes. However, it is important to acknowledge that these hPSC-derived astrocytes exhibit notable differences across studies and when compared to their in vivo counterparts. These differences may potentially compromise translational outcomes if not carefully accounted for. This review aims to explore state-of-the-art in vitro models of human astrocyte development, focusing on the developmental processes, functional maturity, and technical aspects of various hPSC-derived astrocyte differentiation protocols. Additionally, it summarizes their successful application in modeling neurological disorders. The discussion extends to recent advancements in the large-scale production of human astrocytes and their application in developing high-throughput assays conducive to therapeutic drug discovery.

Developmental isoform diversity in the human neocortex informs neuropsychiatric risk mechanisms

RNA splicing is highly prevalent in the brain and has strong links to neuropsychiatric disorders; yet, the role of cell type-specific splicing and transcript-isoform diversity during human brain development has not been systematically investigated. In this work, we leveraged single-molecule long-read sequencing to deeply profile the full-length transcriptome of the germinal zone and cortical plate regions of the developing human neocortex at tissue and single-cell resolution. We identified 214,516 distinct isoforms, of which 72.6% were novel (not previously annotated in Gencode version 33), and uncovered a substantial contribution of transcript-isoform diversity-regulated by RNA binding proteins-in defining cellular identity in the developing neocortex. We leveraged this comprehensive isoform-centric gene annotation to reprioritize thousands of rare de novo risk variants and elucidate genetic risk mechanisms for neuropsychiatric disorders.

Characterizing dysregulations via cell-cell communications in Alzheimer's brains using single-cell transcriptomes

BACKGROUND

Alzheimer's disease (AD) is a devastating neurodegenerative disorder affecting 44 million people worldwide, leading to cognitive decline, memory loss, and significant impairment in daily functioning. The recent single-cell sequencing technology has revolutionized genetic and genomic resolution by enabling scientists to explore the diversity of gene expression patterns at the finest resolution. Most existing studies have solely focused on molecular perturbations within each cell, but cells live in microenvironments rather than in isolated entities. Here, we leveraged the large-scale and publicly available single-nucleus RNA sequencing in the human prefrontal cortex to investigate cell-to-cell communication in healthy brains and their perturbations in AD. We uniformly processed the snRNA-seq with strict QCs and labeled canonical cell types consistent with the definitions from the BRAIN Initiative Cell Census Network. From ligand and receptor gene expression, we built a high-confidence cell-to-cell communication network to investigate signaling differences between AD and healthy brains.

RESULTS

Specifically, we first performed broad communication pattern analyses to highlight that biologically related cell types in normal brains rely on largely overlapping signaling networks and that the AD brain exhibits the irregular inter-mixing of cell types and signaling pathways. Secondly, we performed a more focused cell-type-centric analysis and found that excitatory neurons in AD have significantly increased their communications to inhibitory neurons, while inhibitory neurons and other non-neuronal cells globally decreased theirs to all cells. Then, we delved deeper with a signaling-centric view, showing that canonical signaling pathways CSF, TGFβ, and CX3C are significantly dysregulated in their signaling to the cell type microglia/PVM and from endothelial to neuronal cells for the WNT pathway. Finally, after extracting 23 known AD risk genes, our intracellular communication analysis revealed a strong connection of extracellular ligand genes APP, APOE, and PSEN1 to intracellular AD risk genes TREM2, ABCA1, and APP in the communication from astrocytes and microglia to neurons.

CONCLUSIONS

In summary, with the novel advances in single-cell sequencing technologies, we show that cellular signaling is regulated in a cell-type-specific manner and that improper regulation of extracellular signaling genes is linked to intracellular risk genes, giving the mechanistic intra- and inter-cellular picture of AD.

The broken Alzheimer's disease genome

The complex pathobiology of late-onset Alzheimer's disease (AD) poses significant challenges to therapeutic and preventative interventions. Despite these difficulties, genomics and related disciplines are allowing fundamental mechanistic insights to emerge with clarity, particularly with the introduction of high-resolution sequencing technologies. After all, the disrupted processes at the interface between DNA and gene expression, which we call the broken AD genome, offer detailed quantitative evidence unrestrained by preconceived notions about the disease. In addition to highlighting biological pathways beyond the classical pathology hallmarks, these advances have revitalized drug discovery efforts and are driving improvements in clinical tools. We review genetic, epigenomic, and gene expression findings related to AD pathogenesis and explore how their integration enables a better understanding of the multicellular imbalances contributing to this heterogeneous condition. The frontiers opening on the back of these research milestones promise a future of AD care that is both more personalized and predictive.

Vagus nerve stimulation enhances remyelination and decreases innate neuroinflammation in lysolecithin-induced demyelination

BACKGROUND

Current treatments for Multiple Sclerosis (MS) poorly address chronic innate neuroinflammation nor do they offer effective remyelination. The vagus nerve has a strong regulatory role in inflammation and Vagus Nerve Stimulation (VNS) has potential to affect both neuroinflammation and remyelination in MS.

OBJECTIVE

This study investigated the effects of VNS on demyelination and innate neuroinflammation in a validated MS rodent model.

METHODS

Lysolecithin (LPC) was injected in the corpus callosum (CC) of 46 Lewis rats, inducing a demyelinated lesion. 33/46 rats received continuously-cycled VNS (cVNS) or one-minute per day VNS (1minVNS) or sham VNS from 2 days before LPC-injection until perfusion at 3 days post-injection (dpi) (corresponding with a demyelinated lesion with peak inflammation). 13/46 rats received cVNS or sham from 2 days before LPC-injection until perfusion at 11 dpi (corresponding with a partial remyelinated lesion). Immunohistochemistry and proteomics analyses were performed to investigate the extend of demyelination and inflammation.

RESULTS

Immunohistochemistry showed that cVNS significantly reduced microglial and astrocytic activation in the lesion and lesion border, and significantly reduced the Olig2+ cell count at 3 dpi. Furthermore, cVNS significantly improved remyelination with 57.4 % versus sham at 11 dpi. Proteomic gene set enrichment analyses showed increased activation of (glutamatergic) synapse pathways in cVNS versus sham, most pronounced at 3 dpi.

CONCLUSION

cVNS improved remyelination of an LPC-induced lesion. Possible mechanisms might include modulation of microglia and astrocyte activity, increased (glutamatergic) synapses and enhanced oligodendrocyte clearance after initial injury.

Identifying tumor type and cell type-specific gene expression alterations in pediatric central nervous system tumors

Central nervous system (CNS) tumors are the leading cause of pediatric cancer death, and these patients have an increased risk for developing secondary neoplasms. Due to the low prevalence of pediatric CNS tumors, major advances in targeted therapies have been lagging compared to other adult tumors. We collect single nuclei RNA-seq data from 84,700 nuclei of 35 pediatric CNS tumors and three non-tumoral pediatric brain tissues and characterize tumor heterogeneity and transcriptomic alterations. We distinguish cell subpopulations associated with specific tumor types including radial glial cells in ependymomas and oligodendrocyte precursor cells in astrocytomas. In tumors, we observe pathways important in neural stem cell-like populations, a cell type previously associated with therapy resistance. Lastly, we identify transcriptomic alterations among pediatric CNS tumor types compared to non-tumor tissues, while accounting for cell type effects on gene expression. Our results suggest potential tumor type and cell type-specific targets for pediatric CNS tumor treatment. Here we address current gaps in understanding single nuclei gene expression profiles of previously under-investigated tumor types and enhance current knowledge of gene expression profiles of single cells of various pediatric CNS tumors.

Identity and nature of neural stem cells in the adult human subventricular zone

The existence of neural stem cells (NSCs) in adult human brain neurogenic regions remains unresolved. To address this, we created a cell atlas of the adult human subventricular zone (SVZ) derived from fresh neurosurgical samples using single-cell transcriptomics. We discovered 2 adult radial glia (RG)-like populations, aRG1 and aRG2. aRG1 shared features with fetal early RG (eRG) and aRG2 were transcriptomically similar to fetal outer RG (oRG). We also captured early neuronal and oligodendrocytic NSC states. We found that the biological programs driven by their transcriptomes support their roles as early lineage NSCs. Finally, we show that these NSCs have the potential to transition between states and along lineage trajectories. These data reveal that multipotent NSCs reside in the adult human SVZ.

Ischemic stroke pathophysiology: A bibliometric and visualization analysis from 1990 to 2022

Background

Pathophysiology plays a significant role in the scientific study of ischemic stroke, and has attracted increasing interest from researchers in the field. However, a comprehensive bibliometric analysis is lacking in this field. The purpose of this study is to identify the current research status and hotspots of ischemic stroke pathophysiology from a bibliometric perspective.

Methods

The Web of Science Core Collection database was searched for articles published from 1990 to 2022. CiteSpace, VOSviewer, and R package "bibliometrix" software were used to analyze countries/regions, institutions, journals, authors, papers, and keywords to predict the latest trends in ischemic stroke pathophysiology research.

Results

This analysis collected 7578 records of ischemic stroke pathophysiology. China and America emerged as the leading countries in this field, with Harvard University being the most active institution. Among journals and authors in this field, journal Stroke and author Gregory YH Lip published the most papers, while Nature Medicine was the journal with the highest citation per article. Keywords and co-citation clusters were closely related to "central nervous system", "mechanisms", "biochemistry & molecular biology" and "radiology, nuclear medicine & medical imaging", while other related fields, such as peripheral organs damage induced by the central nervous system and rehabilitation after ischemic stroke, require further research efforts.

Conclusion

This is the first bibliometric study that comprehensively mapped out the knowledge structure and development trends of ischemic stroke pathophysiology in recent 32 years, which may provide a reference for scholars to explore ischemic stroke pathophysiology.

CIRI-Deep Enables Single-Cell and Spatial Transcriptomic Analysis of Circular RNAs with Deep Learning

Circular RNAs (circRNAs) are a crucial yet relatively unexplored class of transcripts known for their tissue- and cell-type-specific expression patterns. Despite the advances in single-cell and spatial transcriptomics, these technologies face difficulties in effectively profiling circRNAs due to inherent limitations in circRNA sequencing efficiency. To address this gap, a deep learning model, CIRI-deep, is presented for comprehensive prediction of circRNA regulation on diverse types of RNA-seq data. CIRI-deep is trained on an extensive dataset of 25 million high-confidence circRNA regulation events and achieved high performances on both test and leave-out data, ensuring its accuracy in inferring differential events from RNA-seq data. It is demonstrated that CIRI-deep and its adapted version enable various circRNA analyses, including cluster- or region-specific circRNA detection, BSJ ratio map visualization, and trans and cis feature importance evaluation. Collectively, CIRI-deep's adaptability extends to all major types of RNA-seq datasets including single-cell and spatial transcriptomic data, which will undoubtedly broaden the horizons of circRNA research.

Multimodal Nature of the Single-cell Primate Brain Atlas: Morphology, Transcriptome, Electrophysiology, and Connectivity

Primates exhibit complex brain structures that augment cognitive function. The neocortex fulfills high-cognitive functions through billions of connected neurons. These neurons have distinct transcriptomic, morphological, and electrophysiological properties, and their connectivity principles vary. These features endow the primate brain atlas with a multimodal nature. The recent integration of next-generation sequencing with modified patch-clamp techniques is revolutionizing the way to census the primate neocortex, enabling a multimodal neuronal atlas to be established in great detail: (1) single-cell/single-nucleus RNA-seq technology establishes high-throughput transcriptomic references, covering all major transcriptomic cell types; (2) patch-seq links the morphological and electrophysiological features to the transcriptomic reference; (3) multicell patch-clamp delineates the principles of local connectivity. Here, we review the applications of these technologies in the primate neocortex and discuss the current advances and tentative gaps for a comprehensive understanding of the primate neocortex.

Distribution-Agnostic Deep Learning Enables Accurate Single-Cell Data Recovery and Transcriptional Regulation Interpretation

Single-cell RNA sequencing (scRNA-seq) is a robust method for studying gene expression at the single-cell level, but accurately quantifying genetic material is often hindered by limited mRNA capture, resulting in many missing expression values. Existing imputation methods rely on strict data assumptions, limiting their broader application, and lack reliable supervision, leading to biased signal recovery. To address these challenges, authors developed Bis, a distribution-agnostic deep learning model for accurately recovering missing sing-cell gene expression from multiple platforms. Bis is an optimal transport-based autoencoder model that can capture the intricate distribution of scRNA-seq data while addressing the characteristic sparsity by regularizing the cellular embedding space. Additionally, they propose a module using bulk RNA-seq data to guide reconstruction and ensure expression consistency. Experimental results show Bis outperforms other models across simulated and real datasets, showcasing superiority in various downstream analyses including batch effect removal, clustering, differential expression analysis, and trajectory inference. Moreover, Bis successfully restores gene expression levels in rare cell subsets in a tumor-matched peripheral blood dataset, revealing developmental characteristics of cytokine-induced natural killer cells within a head and neck squamous cell carcinoma microenvironment.

A single-cell transcriptome atlas of Lueyang black-bone chicken skin

As the largest organ of the body, the skin participates in various physiological activities, such as barrier function, sensory function, and temperature regulation, thereby maintaining the balance between the body and the natural environment. To date, compositional and transcriptional profiles in chicken skin cells have not been reported. Here, we report detailed transcriptome analyses of cell populations present in the skin of a black-feather chicken and a white-feather chicken using single-cell RNA sequencing (scRNA-seq). By analyzing cluster-specific gene expression profiles, we identified 12 cell clusters, and their corresponding cell types were also characterized. Subsequently, we characterized the subpopulations of keratinocytes, myocytes, mesenchymal cells, fibroblasts, and melanocytes. It is worth noting that we have identified a subpopulation of keratinocytes involved in pigment granule capture and a subpopulation of melanocytes involved in pigment granule deposition, both of which have a higher cell abundance in black-feather chicken compared to white-feather chicken. Meanwhile, we also compared the cellular heterogeneity features of Lueyang black-bone chicken skin with different feather colors. In addition, we also screened out 12 genes those could be potential markers of melanocytes. Finally, we validated the specific expression of SGK1, WNT5A, CTSC, TYR, and LAPTM5 in black-feather chicken, which may be the key candidate genes determining the feather color differentiation of Lueyang black-bone chicken. In summary, this study first revealed the transcriptome characteristics of chicken skin cells via scRNA-seq technology. These datasets provide valuable information for the study of avian skin characteristics and have important implications for future poultry breeding.

APOE3 Christchurch modulates β-catenin/Wnt signaling in iPS cell-derived cerebral organoids from Alzheimer's cases

A patient with the PSEN1 E280A mutation and homozygous for APOE3 Christchurch (APOE3Ch) displayed extreme resistance to Alzheimer's disease (AD) cognitive decline and tauopathy, despite having a high amyloid burden. To further investigate the differences in biological processes attributed to APOE3Ch, we generated induced pluripotent stem (iPS) cell-derived cerebral organoids from this resistant case and a non-protected control, using CRISPR/Cas9 gene editing to modulate APOE3Ch expression. In the APOE3Ch cerebral organoids, we observed a protective pattern from early tau phosphorylation. ScRNA sequencing revealed regulation of Cadherin and Wnt signaling pathways by APOE3Ch, with immunostaining indicating elevated β-catenin protein levels. Further in vitro reporter assays unexpectedly demonstrated that ApoE3Ch functions as a Wnt3a signaling enhancer. This work uncovered a neomorphic molecular mechanism of protection of ApoE3 Christchurch, which may serve as the foundation for the future development of protected case-inspired therapeutics targeting AD and tauopathies.

ApoE maintains neuronal integrity via microRNA and H3K27me3-mediated repression

ApoE regulates neurogenesis, although how it influences genetic programs remains elusive. Cortical neurons induced from isogenic control and ApoE-/- human neural stem cells (NSCs) recapitulated key transcriptomic signatures of in vivo counterparts identified from single-cell human midbrain. Surprisingly, ApoE expression in NSC and neural progenitor cells (NPCs) is not required for differentiation. Instead, ApoE prevents the over-proliferation of non-neuronal cells during extended neuronal culture when it is not expressed. Elevated miR-199a-5p level in ApoE-/- cells lowers the EZH1 protein and the repressive H3K27me3 mark, a phenotype rescued by miR-199a-5p steric inhibitor. Reduced H3K27me3 at genes linked to extracellular matrix organization and angiogenesis in ApoE-/- NPC correlates with their aberrant expression and phenotypes in neurons. Interestingly, the ApoE coding sequence, which contains many predicted miR-199a-5p binding sites, can repress miR-199a-5p without translating into protein. This suggests that ApoE maintains neurons integrity through the target-directed miRNA degradation of miR-199a-5p, imparting the H3K27me3-mediated repression of non-neuronal genes during differentiation.

APOBEC3C is a novel target for the immune treatment of lower-grade gliomas

BACKGROUND

Apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) type 3C (A3C) has been identified as a cancer molecular biomarker in the past decade. However, the practical role of A3C in lower-grade gliomas (LGGs) in improving the clinical outcome remains unclear. This study aims to discuss the function of A3C in immunotherapy in LGGs.

METHODS

The RNA-Sequencing (RNA-seq) and corresponding clinical data were extracted from UCSC Xena and the results were verified in the Chinese Glioma Genome Atlas (CGGA). Weighted gene co-expression network analysis (WGCNA) was used for screening A3C-related genes. Comprehensive bioinformation analyses were performed and multiple levels of expression, survival rate, and biological functions were assessed to explore the functions of A3C.

RESULTS

A3C expression was significantly higher in LGGs than in normal tissues but lower than in glioblastoma (GBM), indicating its role as an independent prognosis predictor for LGGs. Twenty-eight A3C-related genes were found with WGCNA for unsupervised clustering analysis and three modification patterns with different outcomes and immune cell infiltration were identified. A3C and the A3C score were also correlated with immune cell infiltration and the expression of immune checkpoints. In addition, the A3C score was correlated with increased sensitivity to chemotherapy. Single-cell RNA (scRNA) analysis indicated that A3C most probably expresses on immune cells, such as T cells, B cells and macrophage.

CONCLUSIONS

A3C is an immune-related prognostic biomarker in LGGs. Developing drugs to block A3C could enhance the efficiency of immunotherapy and improve disease survival.Abbreviation: A3C: Apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) type 3C; LGGs: lower-grade gliomas; CGGA: Chinese Glioma Genome Atlas; WGCNA: Weighted gene co-expression network analysis; scRNA: Single-cell RNA; HGG: higher-grade glioma; OS: overall survival; TME: tumor microenvironment; KM: Kaplan-Meier; PFI: progression-free interval; IDH: isocitrate dehydrogenase; ROC: receiver operating characteristic; GS: gene significance; MM: module membership; TIMER: Tumor IMmune Estimation Resource; GSVA: gene set variation analysis; ssGSEA: single-sample gene-set enrichment analysis; PCA: principal component analysis; AUC: area under ROC curve; HAVCR2: hepatitis A virus cellular receptor 2; PDCD1: programmed cell death 1; PDCD1LG2: PDCD1 ligand 2; PTPRC: protein tyrosine phosphatase receptor type C; ACC: Adrenocortical carcinoma; BLCA: Bladder Urothelial Carcinoma;BRCA: Breast invasive carcinoma; CESC: Cervical squamous cell carcinoma and endocervical adenocarcinoma; CHOLCholangiocarcinoma; COADColon adenocarcinoma; DLBC: Lymphoid Neoplasm Diffuse Large B-cell Lymphoma; ESCA: Esophageal carcinoma; GBM: Glioblastoma multiforme; HNSC: Head and Neck squamous cell carcinoma; KICH: Kidney Chromophobe; KIRC: Kidney renal clear cell carcinoma; KIRP: Kidney renal papillary cell carcinoma; LAML: Acute Myeloid Leukemia; LGG: Brain Lower Grade Glioma; LIHC: Liver hepatocellular carcinoma; LUAD: Lung adenocarcinoma; LUSC: Lung squamous cell carcinoma; MESO: Mesothelioma; OV: Ovarian serous cystadenocarcinoma; PAAD: Pancreatic adenocarcinoma; PCPG: Pheochromocytoma and Paraganglioma; PRAD: Prostate adenocarcinoma; READ: Rectum adenocarcinoma; SARC: Sarcoma; SKCM: Skin Cutaneous Melanoma; STAD: Stomach adenocarcinoma; TGCT: Testicular Germ Cell Tumors; THCA: Thyroid carcinoma; THYM: Thymoma; UCEC: Uterine Corpus Endometrial Carcinoma; UCS: Uterine Carcinosarcoma; UVM: Uveal Melanoma.

Identification of robust cellular programs using reproducible LDA that impact sex-specific disease progression in different genotypes of a mouse model of AD

The gene expression profiles of distinct cell types reflect complex genomic interactions among multiple simultaneous biological processes within each cell that can be altered by disease progression as well as genetic background. The identification of these active cellular programs is an open challenge in the analysis of single-cell RNA-seq data. Latent Dirichlet Allocation (LDA) is a generative method used to identify recurring patterns in counts data, commonly referred to as topics that can be used to interpret the state of each cell. However, LDA's interpretability is hindered by several key factors including the hyperparameter selection of the number of topics as well as the variability in topic definitions due to random initialization. We developed Topyfic, a Reproducible LDA (rLDA) package, to accurately infer the identity and activity of cellular programs in single-cell data, providing insights into the relative contributions of each program in individual cells. We apply Topyfic to brain single-cell and single-nucleus datasets of two 5xFAD mouse models of Alzheimer's disease crossed with C57BL6/J or CAST/EiJ mice to identify distinct cell types and states in different cell types such as microglia. We find that 8-month 5xFAD/Cast F1 males show higher level of microglial activation than matching 5xFAD/BL6 F1 males, whereas female mice show similar levels of microglial activation. We show that regulatory genes such as TFs, microRNA host genes, and chromatin regulatory genes alone capture cell types and cell states. Our study highlights how topic modeling with a limited vocabulary of regulatory genes can identify gene expression programs in single-cell data in order to quantify similar and divergent cell states in distinct genotypes.

Temporal transcriptomic dynamics in developing macaque neocortex

Despite intense research on mice, the transcriptional regulation of neocortical neurogenesis remains limited in humans and non-human primates. Cortical development in rhesus macaque is known to recapitulate multiple facets of cortical development in humans, including the complex composition of neural stem cells and the thicker supragranular layer. To characterize temporal shifts in transcriptomic programming responsible for differentiation from stem cells to neurons, we sampled parietal lobes of rhesus macaque at E40, E50, E70, E80, and E90, spanning the full period of prenatal neurogenesis. Single-cell RNA sequencing produced a transcriptomic atlas of developing parietal lobe in rhesus macaque neocortex. Identification of distinct cell types and neural stem cells emerging in different developmental stages revealed a terminally bifurcating trajectory from stem cells to neurons. Notably, deep-layer neurons appear in the early stages of neurogenesis, while upper-layer neurons appear later. While these different lineages show overlap in their differentiation program, cell fates are determined post-mitotically. Trajectories analysis from ventricular radial glia (vRGs) to outer radial glia (oRGs) revealed dynamic gene expression profiles and identified differential activation of BMP, FGF, and WNT signaling pathways between vRGs and oRGs. These results provide a comprehensive overview of the temporal patterns of gene expression leading to different fates of radial glial progenitors during neocortex layer formation.

Variable expression of MECP2, CDKL5, and FMR1 in the human brain: Implications for gene restorative therapies

MECP2, CDKL5, and FMR1 are three X-linked neurodevelopmental genes associated with Rett, CDKL5-, and fragile-X syndrome, respectively. These syndromes are characterized by distinct constellations of severe cognitive and neurobehavioral anomalies, reflecting the broad but unique expression patterns of each of the genes in the brain. As these disorders are not thought to be neurodegenerative and may be reversible, a major goal has been to restore expression of the functional proteins in the patient's brain. Strategies have included gene therapy, gene editing, and selective Xi-reactivation methodologies. However, tissue penetration and overall delivery to various regions of the brain remain challenging for each strategy. Thus, gaining insights into how much restoration would be required and what regions/cell types in the brain must be targeted for meaningful physiological improvement would be valuable. As a step toward addressing these questions, here we perform a meta-analysis of single-cell transcriptomics data from the human brain across multiple developmental stages, in various brain regions, and in multiple donors. We observe a substantial degree of expression variability for MECP2, CDKL5, and FMR1 not only across cell types but also between donors. The wide range of expression may help define a therapeutic window, with the low end delineating a minimum level required to restore physiological function and the high end informing toxicology margin. Finally, the inter-cellular and inter-individual variability enable identification of co-varying genes and will facilitate future identification of biomarkers.

IDHwt glioblastomas can be stratified by their transcriptional response to standard treatment, with implications for targeted therapy

BACKGROUND

Glioblastoma (GBM) brain tumors lacking IDH1 mutations (IDHwt) have the worst prognosis of all brain neoplasms. Patients receive surgery and chemoradiotherapy but tumors almost always fatally recur.

RESULTS

Using RNA sequencing data from 107 pairs of pre- and post-standard treatment locally recurrent IDHwt GBM tumors, we identify two responder subtypes based on longitudinal changes in gene expression. In two thirds of patients, a specific subset of genes is upregulated from primary to recurrence (Up responders), and in one third, the same genes are downregulated (Down responders), specifically in neoplastic cells. Characterization of the responder subtypes indicates subtype-specific adaptive treatment resistance mechanisms that are associated with distinct changes in the tumor microenvironment. In Up responders, recurrent tumors are enriched in quiescent proneural GBM stem cells and differentiated neoplastic cells, with increased interaction with the surrounding normal brain and neurotransmitter signaling, whereas Down responders commonly undergo mesenchymal transition. ChIP-sequencing data from longitudinal GBM tumors suggests that the observed transcriptional reprogramming could be driven by Polycomb-based chromatin remodeling rather than DNA methylation.

CONCLUSIONS

We show that the responder subtype is cancer-cell intrinsic, recapitulated in in vitro GBM cell models, and influenced by the presence of the tumor microenvironment. Stratifying GBM tumors by responder subtype may lead to more effective treatment.

A New Graph Autoencoder-Based Consensus-Guided Model for scRNA-seq Cell Type Detection

Single-cell RNA sequencing (scRNA-seq) technology is famous for providing a microscopic view to help capture cellular heterogeneity. This characteristic has advanced the field of genomics by enabling the delicate differentiation of cell types. However, the properties of single-cell datasets, such as high dropout events, noise, and high dimensionality, are still a research challenge in the single-cell field. To utilize single-cell data more efficiently and to better explore the heterogeneity among cells, a new graph autoencoder (GAE)-based consensus-guided model (scGAC) is proposed in this article. The data are preprocessed into multiple top-level feature datasets. Then, feature learning is performed by using GAEs to generate new feature matrices, followed by similarity learning based on distance fusion methods. The learned similarity matrices are fed back to the GAEs to guide their feature learning process. Finally, the abovementioned steps are iterated continuously to integrate the final consistent similarity matrix and perform other related downstream analyses. The scGAC model can accurately identify critical features and effectively preserve the internal structure of the data. This can further improve the accuracy of cell type identification.

Mapping Cell Atlases at the Single-Cell Level

Recent advancements in single-cell technologies have led to rapid developments in the construction of cell atlases. These atlases have the potential to provide detailed information about every cell type in different organisms, enabling the characterization of cellular diversity at the single-cell level. Global efforts in developing comprehensive cell atlases have profound implications for both basic research and clinical applications. This review provides a broad overview of the cellular diversity and dynamics across various biological systems. In addition, the incorporation of machine learning techniques into cell atlas analyses opens up exciting prospects for the field of integrative biology.

Single cell transcriptomic representation of social dominance in prefrontal cortex and the influence of preweaning maternal and postweaning social environment

Social dominance encompasses winning dyadic contests and gaining priority access to resources and reproduction. Dominance is influenced by environmental factors, particularly during early postnatal life and adolescence. A disinhibitory medial prefrontal cortex (mPFC) microcircuit has been implicated in the expression of dominance in the "tube test" social competition paradigm in mice, but the neuroplasticity underlying dominance is not known. We previously reported that male pups raised by physically active (wheel-running, as opposed to sedentary) dams exhibit tube test dominance and increased reproductive fitness, and here we show that social isolation from weaning also increases dominance. By using single cell transcriptomics, we tested if increased dominance in these models is associated with a specific transcriptional profile in one or more cell-types in the mPFC. The preweaning maternal effect, but not postweaning social isolation, caused gene expression changes in pyramidal neurons. However, both the effect of maternal exercise and social isolation induced the coordinated downregulation of synaptic channel, receptor, and adhesion genes in parvalbumin positive (PV) interneurons, suggesting that development of dominance is accompanied by impaired PV interneuron-mediated inhibition of pyramidal cells. This study may help understand environmentally induced transcriptional plasticity in the PFC and its relationship to tube test dominance.

Glioblastoma evolution and heterogeneity from a 3D whole-tumor perspective

Treatment failure for the lethal brain tumor glioblastoma (GBM) is attributed to intratumoral heterogeneity and tumor evolution. We utilized 3D neuronavigation during surgical resection to acquire samples representing the whole tumor mapped by 3D spatial coordinates. Integrative tissue and single-cell analysis revealed sources of genomic, epigenomic, and microenvironmental intratumoral heterogeneity and their spatial patterning. By distinguishing tumor-wide molecular features from those with regional specificity, we inferred GBM evolutionary trajectories from neurodevelopmental lineage origins and initiating events such as chromothripsis to emergence of genetic subclones and spatially restricted activation of differential tumor and microenvironmental programs in the core, periphery, and contrast-enhancing regions. Our work depicts GBM evolution and heterogeneity from a 3D whole-tumor perspective, highlights potential therapeutic targets that might circumvent heterogeneity-related failures, and establishes an interactive platform enabling 360° visualization and analysis of 3D spatial patterns for user-selected genes, programs, and other features across whole GBM tumors.

STAB2: an updated spatio-temporal cell atlas of the human and mouse brain

The brain is constituted of heterogeneous types of neuronal and non-neuronal cells, which are organized into distinct anatomical regions, and show precise regulation of gene expression during development, aging and function. In the current database release, STAB2 provides a systematic cellular map of the human and mouse brain by integrating recently published large-scale single-cell and single-nucleus RNA-sequencing datasets from diverse regions and across lifespan. We applied a hierarchical strategy of unsupervised clustering on the integrated single-cell transcriptomic datasets to precisely annotate the cell types and subtypes in the human and mouse brain. Currently, STAB2 includes 71 and 61 different cell subtypes defined in the human and mouse brain, respectively. It covers 63 subregions and 15 developmental stages of human brain, and 38 subregions and 30 developmental stages of mouse brain, generating a comprehensive atlas for exploring spatiotemporal transcriptomic dynamics in the mammalian brain. We also augmented web interfaces for querying and visualizing the gene expression in specific cell types. STAB2 is freely available at https://mai.fudan.edu.cn/stab2.

Spatiotemporal transcriptome atlas reveals the regional specification of the developing human brain

Different functional regions of brain are fundamental for basic neurophysiological activities. However, the regional specification remains largely unexplored during human brain development. Here, by combining spatial transcriptomics (scStereo-seq) and scRNA-seq, we built a spatiotemporal developmental atlas of multiple human brain regions from 6-23 gestational weeks (GWs). We discovered that, around GW8, radial glia (RG) cells have displayed regional heterogeneity and specific spatial distribution. Interestingly, we found that the regional heterogeneity of RG subtypes contributed to the subsequent neuronal specification. Specifically, two diencephalon-specific subtypes gave rise to glutamatergic and GABAergic neurons, whereas subtypes in ventral midbrain were associated with the dopaminergic neurons. Similar GABAergic neuronal subtypes were shared between neocortex and diencephalon. Additionally, we revealed that cell-cell interactions between oligodendrocyte precursor cells and GABAergic neurons influenced and promoted neuronal development coupled with regional specification. Altogether, this study provides comprehensive insights into the regional specification in the developing human brain.

Human brain organoid model of maternal immune activation identifies radial glia cells as selectively vulnerable

Maternal immune activation (MIA) during critical windows of gestation is correlated with long-term neurodevelopmental deficits in the offspring, including increased risk for autism spectrum disorder (ASD) in humans. Interleukin 6 (IL-6) derived from the gestational parent is one of the major molecular mediators by which MIA alters the developing brain. In this study, we establish a human three-dimensional (3D) in vitro model of MIA by treating induced pluripotent stem cell-derived dorsal forebrain organoids with a constitutively active form of IL-6, Hyper-IL-6. We validate our model by showing that dorsal forebrain organoids express the molecular machinery necessary for responding to Hyper-IL-6 and activate STAT signaling upon Hyper-IL-6 treatment. RNA sequencing analysis reveals the upregulation of major histocompatibility complex class I (MHCI) genes in response to Hyper-IL-6 exposure, which have been implicated with ASD. We find a small increase in the proportion of radial glia cells after Hyper-IL-6 treatment through immunohistochemistry and single-cell RNA-sequencing. We further show that radial glia cells are the cell type with the highest number of differentially expressed genes, and Hyper-IL-6 treatment leads to the downregulation of genes related to protein translation in line with a mouse model of MIA. Additionally, we identify differentially expressed genes not found in mouse models of MIA, which might drive species-specific responses to MIA. Finally, we show abnormal cortical layering as a long-term consequence of Hyper-IL-6 treatment. In summary, we establish a human 3D model of MIA, which can be used to study the cellular and molecular mechanisms underlying the increased risk for developing disorders such as ASD.

Spatiotemporal characterization of glial cell activation in an Alzheimer's disease model by spatially resolved transcriptomics

The molecular changes that occur with the progression of Alzheimer's disease (AD) are well known, but an understanding of the spatiotemporal heterogeneity of changes in the brain is lacking. Here, we investigated the spatially resolved transcriptome in a 5XFAD AD model at different ages to understand regional changes at the molecular level. Spatially resolved transcriptomic data were obtained from 5XFAD AD models and age-matched control mice. Differentially expressed genes were identified using spots clustered by anatomical structures. Gene signatures of activation of microglia and astrocytes were calculated and mapped on the spatially resolved transcriptomic data. We identified early alterations in the white matter (WM) of the AD model before the definite accumulation of amyloid plaques in the gray matter (GM). Changes in the early stage of the disease involved primarily glial cell activation in the WM, whereas the changes in the later stage of pathology were prominent in the GM. We confirmed that disease-associated microglia (DAM) and astrocyte (DAA) signatures also showed initial changes in WM and that activation spreads to GM. Trajectory inference using microglial gene sets revealed the subdivision of DAMs with different spatial patterns. Taken together, these results help to understand the spatiotemporal changes associated with reactive glial cells as a major pathophysiological characteristic of AD. The heterogeneous spatial molecular changes apply to identifying diagnostic and therapeutic targets caused by amyloid accumulation in AD.

scFED: Clustering Identifying Cell Types of scRNA-Seq Data Based on Feature Engineering Denoising

Recently developed single-cell RNA-seq (scRNA-seq) technology has given researchers the chance to investigate single-cell level of disease development. Clustering is one of the most essential strategies for analyzing scRNA-seq data. Choosing high-quality feature sets can significantly enhance the outcomes of single-cell clustering and classification. But computationally burdensome and highly expressed genes cannot afford a stabilized and predictive feature set for technical reasons. In this study, we introduce scFED, a feature-engineered gene selection framework. scFED identifies prospective feature sets to eliminate the noise fluctuation. And fuse them with existing knowledge from the tissue-specific cellular taxonomy reference database (CellMatch) to avoid the influence of subjective factors. Then present a reconstruction approach for noise reduction and crucial information amplification. We apply scFED on four genuine single-cell datasets and compare it with other techniques. According to the results, scFED improves clustering, decreases dimension of the scRNA-seq data, improves cell type identification when combined with clustering algorithms, and has higher performance than other methods. Therefore, scFED offers certain benefits in scRNA-seq data gene selection.

Truncated radial glia as a common precursor in the late corticogenesis of gyrencephalic mammals

The diversity of neural stem cells is a hallmark of the cerebral cortex development in gyrencephalic mammals, such as Primates and Carnivora. Among them, ferrets are a good model for mechanistic studies. However, information on their neural progenitor cells (NPC), termed radial glia (RG), is limited. Here, we surveyed the temporal series of single-cell transcriptomes of progenitors regarding ferret corticogenesis and found a conserved diversity and temporal trajectory between human and ferret NPC, despite the large timescale difference. We found truncated RG (tRG) in ferret cortical development, a progenitor subtype previously described in humans. The combination of in silico and in vivo analyses identified that tRG differentiate into both ependymal and astrogenic cells. Via transcriptomic comparison, we predict that this is also the case in humans. Our findings suggest that tRG plays a role in the formation of adult ventricles, thereby providing the architectural bases for brain expansion.

Single-cell analysis reveals specific neuronal transition during mouse corticogenesis

Background: Currently, the mechanism(s) underlying corticogenesis is still under characterization. Methods: We curated the most comprehensive single-cell RNA-seq (scRNA-seq) datasets from mouse and human fetal cortexes for data analysis and confirmed the findings with co-immunostaining experiments. Results: By analyzing the developmental trajectories with scRNA-seq datasets in mice, we identified a specific developmental sub-path contributed by a cell-population expressing both deep- and upper-layer neurons (DLNs and ULNs) specific markers, which occurred on E13.5 but was absent in adults. In this cell-population, the percentages of cells expressing DLN and ULN markers decreased and increased, respectively, during the development suggesting direct neuronal transition (namely D-T-U). Whilst genes significantly highly/uniquely expressed in D-T-U cell population were significantly enriched in PTN/MDK signaling pathways related to cell migration. Both findings were further confirmed by co-immunostaining with DLNs, ULNs and D-T-U specific markers across different timepoints. Furthermore, six genes (co-expressed with D-T-U specific markers in mice) showing a potential opposite temporal expression between human and mouse during fetal cortical development were associated with neuronal migration and cognitive functions. In adult prefrontal cortexes (PFC), D-T-U specific genes were expressed in neurons from different layers between humans and mice. Conclusion: Our study characterizes a specific cell population D-T-U showing direct DLNs to ULNs neuronal transition and migration during fetal cortical development in mice. It is potentially associated with the difference of cortical development in humans and mice.

Single-nucleus transcriptome profiling of prefrontal cortex induced by chronic methamphetamine treatment

Background

Methamphetamine (METH) addiction causes a huge burden on society. The prefrontal cortex (PFC), associated with emotion and cognitive behaviours, is also involved in addiction neurocircuitry. Although bulk RNA sequencing has shown METH-induced gene alterations in the mouse PFC, the impact on different cell types remains unknown.

Aims

To clarify the effects of METH treatment on different cell types of the PFC and the potential pathways involved in METH-related disorders.

Methods

We performed single-nucleus RNA sequencing (snRNA-seq) to examine the transcriptomes of 20 465 nuclei isolated from the PFC of chronic METH-treated and control mice. Main cell types and differentially expressed genes (DEGs) were identified and confirmed by RNA fluorescence in situ hybridization(FISH).

Results

Six main cell types were identified depending on the single-cell nucleus sequencing; of particular interest were the mature oligodendrocytes in the PFC. The DEGs of mature oligodendrocytes were enriched in the myelin sheath, adenosine triphosphate (ATP) metabolic process, mitochondrial function and components, and so on. The messenger RNA levels of Aldoc and Atp5l (FISH) and the protein level of the mitochondrial membrane pore subunit TOM40 (immunofluorescence) decreased in the mature oligodendrocytes. Fast blue staining and transmission electron microscopy image indicated myelin damage, and the myelin thickness decreased in METH brains.

Conclusions

snRNA-seq reveals altered transcriptomes of different cell types in mouse PFC induced by chronic METH treatment, underscoring potential relationships with psychiatric disorders.

Functional genomics and systems biology in human neuroscience

Neuroscience research has entered a phase of key discoveries in the realm of neurogenomics owing to strong financial and intellectual support for resource building and tool development. The previous challenge of tissue heterogeneity has been met with the application of techniques that can profile individual cells at scale. Moreover, the ability to perturb genes, gene regulatory elements and neuronal activity in a cell-type-specific manner has been integrated with gene expression studies to uncover the functional underpinnings of the genome at a systems level. Although these insights have necessarily been grounded in model systems, we now have the opportunity to apply these approaches in humans and in human tissue, thanks to advances in human genetics, brain imaging and tissue collection. We acknowledge that there will probably always be limits to the extent to which we can apply the genomic tools developed in model systems to human neuroscience; however, as we describe in this Perspective, the neuroscience field is now primed with an optimal foundation for tackling this ambitious challenge. The application of systems-level network analyses to these datasets will facilitate a deeper appreciation of human neurogenomics that cannot otherwise be achieved from directly observable phenomena.